We investigated the impact of physiologic noise correction on PCC seeded co-activation pattern (CAP) analysis varying the cluster number. We found that patterns from PCC seeded CAP analysis were best classified as 5 sub-patterns of default mode, sensory visual and motor, salience, central executive networks and noise. Also we observed that physiologic noise correction resulted in less frequent salience and central executive networks from PCC-related co-activations than uncorrected data.
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